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Medical artificial intelligence is as much social as it is technological

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Despite the promise of medical artificial intelligence applications, their acceptance in real-world clinical settings is low, with lack of transparency and trust being barriers that need to be overcome. We discuss the importance of the collaborative process in medical artificial intelligence, whereby experts from various fields work together and tackle transparency issues and build trust over time.

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Acknowledgements

We thank J. Anderson for helpful feedback. The research informing this Comment was supported by a Wellcome Grant for the project ‘AI in the Clinic’ (grant number WT/213606).

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Authors and Affiliations

  1. Interchange Research, University College London, London, UK

    Annamaria Carusi

  2. University of Bristol, Bristol, UK

    Peter D. Winter

  3. Sheffield Teaching Hospitals, Sheffield, UK

    Iain Armstrong, David G. Kiely & Andy Swift

  4. Università di Torino, Dipartimento di Informatica, Turin, Italy

    Fabio Ciravegna

  5. University of Sheffield, Sheffield, UK

    David G. Kiely, Haiping Lu, Ian Sabroe & Andy Swift

  6. Imperial College London, London, UK

    Allan Lawrie

Authors
  1. Annamaria Carusi
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  2. Peter D. Winter
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  3. Iain Armstrong
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  4. Fabio Ciravegna
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  5. David G. Kiely
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  6. Allan Lawrie
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  7. Haiping Lu
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  8. Ian Sabroe
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  9. Andy Swift
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Correspondence to Peter D. Winter.

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The authors declare no competing interests.

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Nature Machine Intelligence thanks James Anderson for their contribution to the peer review of this work.

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Carusi, A., Winter, P.D., Armstrong, I. et al. Medical artificial intelligence is as much social as it is technological. Nat Mach Intell 5, 98–100 (2023). https://doi.org/10.1038/s42256-022-00603-3

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